摘要
针对半间歇反应过程参数时变问题,研究基于Markov参数整定的单神经元自适应迭代学习PID控制方法。首先建立二维迭代学习PID控制器(2D-ILC-PID),采用Markov参数法离线整定控制器的参数初值;然后在批次内采用单神经元自适应调节机制在线调节2D-ILC-PID控制器参数,同时利用批次间的重复特性更新控制输入提高迭代学习速率,有效提升控制系统跟踪性能。最后在环己胺制备反应过程进行仿真实验验证,实验结果表明提出的基于Markov参数整定的自适应迭代学习控制方法能够实现多时段反应器温度的精确跟踪。
Parameters of semi-batch processes often varies with time. A single neuron adaptive PID iterative learning control strategy based on Markov parameter tuning was investigated in this study. A two-dimensional iterative learning PID controller(2D-ILC-PID) was first established, and the initial values of the parameters were tuned offline by the Markov parameter method. The controller parameters were adaptively adjusted online by single neuron adaptive adjustment mechanism. The algorithm can make full use of the repeating information between batches and improve the iterative learning rate, and achieve effective improvement of the control performance. The control method was verified by a simulated reaction process, and the results show that the single neuron adaptive iterative learning control method based on Markov parameter tuning can effectively achieve accurate tracking of reaction temperature.
作者
尹俊华
薄翠梅
刘艳萍
杨磊
YIN Jun-hua;BO Cui-mei;LIU Yan-ping;YANG Lei(College of Electrical Engineering and Control Science,Nanjing University of Technology,Nanjing 211816,China)
出处
《高校化学工程学报》
EI
CAS
CSCD
北大核心
2019年第6期1490-1498,共9页
Journal of Chemical Engineering of Chinese Universities
基金
国家自然科学基金(61673205,21727818)
